activity
20182021
most citedReinforcement Learning on Variable Impedance Controller for High-Precision Robotic Assembly

20 citations · 25 across the 5 of their papers we have counts for

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7 papers · 1 filter

cs.RO20212 cited

Kit-Net: Self-Supervised Learning to Kit Novel 3D Objects into Novel 3D Cavities

Shivin Devgon, Jeffrey Ichnowski, Michael Danielczuk +6

In industrial part kitting, 3D objects are inserted into cavities for transportation or subsequent assembly. Kitting is a critical step as it can decrease downstream processing and…

cs.RO2020

Information-Collection in Robotic Process Monitoring: An Active Perception Approach

Martin A. Sehr, Wei Xi Xia, Prithvi Akella +2

Active perception systems maximizing information gain to support both monitoring and decision making have seen considerable application in recent work. In this paper, we propose an…

cs.RO2020

Industrial Robot Grasping with Deep Learning using a Programmable Logic Controller (PLC)

Eugen Solowjow, Ines Ugalde, Yash Shahapurkar +5

Universal grasping of a diverse range of previously unseen objects from heaps is a grand challenge in e-commerce order fulfillment, manufacturing, and home service robotics. Recent…

cs.RO2019

UniGrasp: Learning a Unified Model to Grasp with Multifingered Robotic Hands

Lin Shao, Fabio Ferreira, Mikael Jorda +6

To achieve a successful grasp, gripper attributes such as its geometry and kinematics play a role as important as the object geometry. The majority of previous work has focused on…

cs.RO2019

Deep Reinforcement Learning for Industrial Insertion Tasks with Visual Inputs and Natural Rewards

Gerrit Schoettler, Ashvin Nair, Jianlan Luo +4

Connector insertion and many other tasks commonly found in modern manufacturing settings involve complex contact dynamics and friction. Since it is difficult to capture related phy…

cs.RO201920 cited

Reinforcement Learning on Variable Impedance Controller for High-Precision Robotic Assembly

Jianlan Luo, Eugen Solowjow, Chengtao Wen +4

Precise robotic manipulation skills are desirable in many industrial settings, reinforcement learning (RL) methods hold the promise of acquiring these skills autonomously. In this…